# 🍔🧠 What's inside an LLM's KV cache

DevFeed: [🍔🧠 What's inside an LLM's KV cache](<https://devfeed.tech/articles/what-s-inside-an-llm-s-kv-cache-18137.md>)

Original publisher: [Read original article](<https://hungrymindsdev.substack.com/p/whats-inside-an-llms-kv-cache>)

Author: Alexandre Zajac

Published: 2026-08-10T15:30:59Z

Content type: article

Language: en

Sources: [Hungry Minds](<https://devfeed.tech/sources/hungry-minds.md>)

Topics: [Cache](<https://devfeed.tech/topics/cache.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Inference](<https://devfeed.tech/topics/inference.md>)

Tags: [cache](<https://devfeed.tech/tags/cache.md>), [caching](<https://devfeed.tech/tags/caching.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-performance](<https://devfeed.tech/tags/inference-performance.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llm](<https://devfeed.tech/tags/llm.md>), [models](<https://devfeed.tech/tags/models.md>), [performance](<https://devfeed.tech/tags/performance.md>), [quantization](<https://devfeed.tech/tags/quantization.md>)

## AI overview

The article explains that the KV cache stores key and value vectors for input tokens during LLM inference. Its memory use and bandwidth demands grow with context length and batch size, creating a bottleneck for long-context serving. It discusses grouped-query attention, latent attention, KV cache quantization, paged attention, and prefix caching as ways to reduce memory use, fragmentation, cost, or latency.

## Source excerpt

PLUS: Google's AI depth decline 🧠, Real-time agent load balancing ⚡, Semantic search ranking at scale 👨💻